000			03666nam a22003855i 4500
001			76022
003			ES-MaUEC
005			20230202101844.0
007			cr nn 008mamaa
008			131123s2014 xxu| s |||| 0|eng d
020			_a9781461480945
040			_aES-MaUEC
050		4	_aQP363 _b.C66 2014 EB
245	0	4	_aThe Computing Dendrite : _bFrom Structure to Function _cedited by Hermann Cuntz, Michiel W.H. Remme, Benjamin Torben-Nielsen
260			_aNew York _bSpringer International Publishing _c2014
300			_a1 recurso en línea (XVIII, 510 p.) 101 il., 66 il. col.
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	1		_aSpringer Series in Computational Neuroscience _x2197-1900 _v11
520			_aNeuronal dendritic trees are complex structures that endow the cell with powerful computing capabilities and allow for high neural interconnectivity. Studying the function of dendritic structures has a long tradition in theoretical neuroscience, starting with the pioneering work by Wilfrid Rall in the 1950s. Recent advances in experimental techniques allow us to study dendrites with a new perspective and in greater detail. The goal of this volume is to provide a résumé of the state-of-the-art in experimental, computational, and mathematical investigations into the functions of dendrites in a variety of neural systems. TheÂ{u2BEF}k firstÂ{uCBEF}ks at morphological properties of dendrites and summarizes the approaches to measure dendrite morphology quantitatively and to actually generate synthetic dendrite morphologies in computer models. This morphological characterization ranges from the study of fractal principles to describe dendrite topologies, to the consequences of optimization principles for dendrite shape. Individual approaches are collected to study the aspects of dendrite shape that relate directly to underlying circuit constraints and computation. The second main theme focuses on how dendrites contribute to the computations that neurons perform. What role do dendritic morphology andÂ{u4A25} distributions of synapses and membrane properties over the dendritic tree have in determining the output of a neuron in response to its input?Â{u1837}wide range of studies is brought together, with topics ranging from general to system-specific phenomenaâ€{u3BED}e having a strong experimental component, and others being fully theoretical. The studies come from many different neural systems and animal species ranging from invertebrates to mammals. WithÂ{u4A29}s broad focus, an overview is given of the diversity of mechanisms that dendrites can employ to shape neural computations.
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGERrevisado
650		7	_aDendritas _9158502 _0comprobar BNE20011336946 _2embne
650	0	7	_aNeurociencia computacional _2embne _9481390
700	1		_aCuntz, Hermann _eeditor _0Local _984829
700	1		_aRemme, Michiel W.H _eeditor literario _984830 _0Local
700	1		_aTorben-Nielsen, Benjamin _eeditor literario _984831 _0Local
830		0	_aSpringer Series in Computational Neuroscience _x2197-1900 _v11 _9133155
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-1-4614-8094-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9781461480945
907			_a.b12816401 _b10-10-17 _c01-10-14
998			_am _a_alco _a_vill _b22-03-17 _cm _dz _eu _feng _gxxu _h4
945			_aQP363 .C66 2014 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11545781 _z06-04-17
999			_c76022 _d76022 _x1